MLOps Engineer overview

Builds and maintains the infrastructure and tooling that enables data scientists and ML engineers to train, evaluate, deploy, and monitor machine learning models in production efficiently. Owns the ML platform stack including experiment tracking, feature stores, model registries, and serving infrastructure. Bridges the operational gap between research and production, ensuring models degrade gracefully and can be retrained and redeployed with minimal friction.